Open Technical Problems in Open-Weight AI Model Risk Management - Stephen Casper; Kyle O'Brien; Shayne Longpre; Elizabeth Seger; Kevin Klyman; Rishi Bommasani; Aniruddha Nrusimha; Ilia Shumailov; Sören Mindermann; Steven Basart; Frank Rudzicz; Kellin Pelrine; et al. (Trans. Mach. Learn. Res., 2026)

Offline Model-Based Optimization: Comprehensive Review - Minsu Kim; Jiayao Gu; Ye Yuan; Taeyoung Yun; Zixuan Liu; Yoshua Bengio; Can Chen (Trans. Mach. Learn. Res., 2026)

Extendable Planning via Multiscale Diffusion - Chang Chen; Hany Hamed; Doojin Baek; Taegu Kang; Samyeul Noh; Yoshua Bengio; Sungjin Ahn (Fortieth AAAI Conference on Artificial Intelligence, Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence, AAAI 2026, Singapore, January 20-27, 2026, 2026)

Artificial Neural Networks and Machine Learning - ICANN 2025 - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I - Walter Senn; Marcello Sanguineti; Ausra Saudargiene; Igor V. Tetko; Alessandro E. P. Villa; Viktor K. Jirsa; Yoshua Bengio (Springer, 2026)

Artificial Neural Networks and Machine Learning - ICANN 2025 - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part II - Walter Senn; Marcello Sanguineti; Ausra Saudargiene; Igor V. Tetko; Alessandro E. P. Villa; Viktor K. Jirsa; Yoshua Bengio (Springer, 2026)

Artificial Neural Networks and Machine Learning - ICANN 2025 - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part III - Walter Senn; Marcello Sanguineti; Ausra Saudargiene; Igor V. Tetko; Alessandro E. P. Villa; Viktor K. Jirsa; Yoshua Bengio (Springer, 2026)

Artificial Neural Networks and Machine Learning - ICANN 2025 - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part IV - Walter Senn; Marcello Sanguineti; Ausra Saudargiene; Igor V. Tetko; Alessandro E. P. Villa; Viktor K. Jirsa; Yoshua Bengio (Springer, 2026)

Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions - 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part V - Walter Senn; Marcello Sanguineti; Ausra Saudargiene; Igor V. Tetko; Alessandro E. P. Villa; Viktor K. Jirsa; Yoshua Bengio (Springer, 2026)

The Future of the AI Summit Series - Lucia Velasco; Charles Martinet; Henry de Zoete; Robert Trager; Duncan Snidal; Ben Garfinkel; Kwan Yee Ng; Haydn Belfield; Don Wallace; Yoshua Bengio; Benjamin Prud'homme; Brian Tse; et al. (CoRR, 2026)

In-Context Reinforcement Learning through Bayesian Fusion of Context and Value Prior - Anaïs Berkes; Vincent Taboga; Donna Vakalis; David Rolnick; Yoshua Bengio (CoRR, 2026)

Discrete Feynman-Kac Correctors - Mohsin Hasan; Viktor Ohanesian; Artem Gazizov; Yoshua Bengio; Alán Aspuru-Guzik; Roberto Bondesan; Marta Skreta; Kirill Neklyudov (CoRR, 2026)

Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies - Miles Brundage; Noemi Dreksler; Aidan Homewood; Sean McGregor; Patricia Paskov; Conrad Stosz; Girish Sastry; A. Feder Cooper; George Balston; Steven Adler; Stephen Casper; Markus Anderljung; et al. (CoRR, 2026)

Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors - Hyeonah Kim; Minsu Kim; Celine Roget; Dionessa Biton; Louis Vaillancourt; Yves V. Brun; Yoshua Bengio; Alex Hernández-García (CoRR, 2026)

When Benign Inputs Lead to Severe Harms: Eliciting Unsafe Unintended Behaviors of Computer-Use Agents - Jaylen Jones; Zhehao Zhang; Yuting Ning; Eric Fosler-Lussier; Pierre-Luc St-Charles; Yoshua Bengio; Dawn Song; Yu Su; Huan Sun (CoRR, 2026)

International AI Safety Report 2026 - Yoshua Bengio; Stephen Clare; Carina Prunkl; Maksym Andriushchenko; Ben Bucknall; Malcolm Murray; Rishi Bommasani; Stephen Casper; Tom Davidson; Raymond Douglas; David Duvenaud; Philip Fox; et al. (CoRR, 2026)

Noticing the Watcher: LLM Agents Can Infer CoT Monitoring from Blocking Feedback - Thomas Jiralerspong; Flemming Kondrup; Yoshua Bengio (CoRR, 2026)

The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning - Donghang Wu; Tianyu Zhang; Yuxin Li; Hexin Liu; Chen Chen; Eng Siong Chng; Yoshua Bengio (CoRR, 2026)

General Multimodal Protein Design Enables DNA-Encoding of Chemistry - Jarrid Rector-Brooks; Théophile Lambert; Marta Skreta; Daniel Roth; Yueming Long; Zi-Qi Li; Xi Zhang; Miruna T. Cretu; Francesca-Zhoufan Li; Tanvi Ganapathy; Emily Jin; Avishek Joey Bose; et al. (CoRR, 2026)

Local Inconsistency Resolution: The Interplay between Attention and Control in Probabilistic Models - Oliver E. Richardson; Mandana Samiei; Mehran Shakerinava; Joseph D. Viviano; Abdessamad El Kabid; Ali Parviz; Yoshua Bengio (CoRR, 2026)

Language models recognize dropout and Gaussian noise applied to their activations - Damiano Fornasiere; Mirko Bronzi; Spencer Kitts; Alessandro Palmas; Yoshua Bengio; Oliver Richardson (CoRR, 2026)

When 2D Tasks Meet 1D Serialization: On Serialization Friction in Structured Tasks - Chung-Hsiang Lo; Lu Li; Diji Yang; Tianyu Zhang; Yunkai Zhang; Yoshua Bengio; Yi Zhang (CoRR, 2026)

Generative Recursive Reasoning - Junyeob Baek; Mingyu Jo; Minsu Kim; Mengye Ren; Yoshua Bengio; Sungjin Ahn (CoRR, 2026)

Adaptive Order Policies for Masked Diffusion - Jama Hussein Mohamud; Mohsin Hasan; Mirco Ravanelli; Yoshua Bengio (CoRR, 2026)

CIAware-Bench: Benchmarking Control Intervention Awareness Across Frontier LLMs - Joachim Schaeffer; Thomas Jiralerspong; Alexander Panfilov; Guillaume Lajoie; Jonas Geiping; Yoshua Bengio; Roland S. Zimmermann (CoRR, 2026)

Open Problems in Technical AI Governance - Anka Reuel; Benjamin Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (Trans. Mach. Learn. Res., 2025)

Low Compute Unlearning via Sparse Representations - Vedant Shah; Frederik Träuble; Ashish Malik; Hugo Larochelle; Michael Curtis Mozer; Sanjeev Arora; Yoshua Bengio; Anirudh Goyal (Trans. Mach. Learn. Res., 2025)

Geometric Signatures of Compositionality Across a Language Model's Lifetime - Jin Hwa Lee; Thomas Jiralerspong; Lei Yu; Yoshua Bengio; Emily Cheng (Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2025, Vienna, Austria, July 27 - August 1, 2025, 2025)

Ant Colony Sampling with GFlowNets for Combinatorial Optimization - Minsu Kim; Sanghyeok Choi; Hyeonah Kim; Jiwoo Son; Jinkyoo Park; Yoshua Bengio (International Conference on Artificial Intelligence and Statistics, AISTATS 2025, Mai Khao, Thailand, 3-5 May 2025, 2025)

A HOT Dataset: 150, 000 Buildings for HVAC Operations Transfer Research - Anaïs Berkes; Yoshua Bengio; David Rolnick; Donna Vakalis (Proceedings of the 12th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2025, Colorado School of Mines, Golden, CO, USA, November 19-21, 2025, 2025)

Adaptive teachers for amortized samplers - Minsu Kim; Sanghyeok Choi; Taeyoung Yun; Emmanuel Bengio; Leo Feng; Jarrid Rector-Brooks; Sungsoo Ahn; Jinkyoo Park; Nikolay Malkin; Yoshua Bengio (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold - Lazar Atanackovic; Xi Zhang; Brandon Amos; Mathieu Blanchette; Leo J. Lee; Yoshua Bengio; Alexander Tong; Kirill Neklyudov (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Action abstractions for amortized sampling - Oussama Boussif; Léna Néhale Ezzine; Joseph D. Viviano; Michal Koziarski; Moksh Jain; Nikolay Malkin; Emmanuel Bengio; Rim Assouel; Yoshua Bengio (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

On the Transfer of Object-Centric Representation Learning - Aniket Rajiv Didolkar; Andrii Zadaianchuk; Anirudh Goyal; Michael Curtis Mozer; Yoshua Bengio; Georg Martius; Maximilian Seitzer (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly - Hongyu Guo; Yoshua Bengio; Shengchao Liu (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning - Seanie Lee; Minsu Kim; Lynn Cherif; David Dobre; Juho Lee; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models - Seanie Lee; Haebin Seong; Dong Bok Lee; Minki Kang; Xiaoyin Chen; Dominik Wagner; Yoshua Bengio; Juho Lee; Sung Ju Hwang (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation - Lu Li; Tianyu Zhang; Zhiqi Bu; Suyuchen Wang; Huan He; Jie Fu; Yonghui Wu; Jiang Bian; Yong Chen; Yoshua Bengio (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets - Zhen Liu; Tim Z. Xiao; Weiyang Liu; Yoshua Bengio; Dinghuai Zhang (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Structure Language Models for Protein Conformation Generation - Jiarui Lu; Xiaoyin Chen; Stephen Zhewen Lu; Chence Shi; Hongyu Guo; Yoshua Bengio; Jian Tang (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Towards Improving Exploration through Sibling Augmented GFlowNets - Kanika Madan; Alex Lamb; Emmanuel Bengio; Glen Berseth; Yoshua Bengio (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text - Tianyu Zhang; Suyuchen Wang; Lu Li; Ge Zhang; Perouz Taslakian; Sai Rajeswar; Jie Fu; Bang Liu; Yoshua Bengio (The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025, 2025)

Rejecting Hallucinated State Targets during Planning - Harry Zhao; Tristan Sylvain; Romain Laroche; Doina Precup; Yoshua Bengio (Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025, 2025)

Towards a Formal Theory of Representational Compositionality - Eric Elmoznino; Thomas Jiralerspong; Yoshua Bengio; Guillaume Lajoie (Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025, 2025)

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models - Siddarth Venkatraman; Mohsin Hasan; Minsu Kim; Luca Scimeca; Marcin Sendera; Yoshua Bengio; Glen Berseth; Nikolay Malkin (Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025, 2025)

Monte Carlo Tree Diffusion for System 2 Planning - Jaesik Yoon; Hyeonseo Cho; Doojin Baek; Yoshua Bengio; Sungjin Ahn (Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025, 2025)

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N - Tianyu Zhang; Andrew Robert Williams; Phillip Wozny; Kai-Hendrik Cohrs; Koen Ponse; Marco Jiralerspong; Soham R. Phade; Sunil Srinivasa; Lu Li; Yang Zhang; Prateek Gupta; Erman Acar; et al. (Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025, 2025)

Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training - Brian R. Bartoldson; Siddarth Venkatraman; James Diffenderfer; Moksh Jain; Tal Ben-Nun; Seanie Lee; Minsu Kim; Johan S. Obando-Ceron; Yoshua Bengio; Bhavya Kailkhura (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, NeurIPS 2025, San Diago, CA, USA, December 2-7, 2025 / Mexico City, Mexico, November 30 - December 5, 2025, 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, NeurIPS 2025, San Diago, CA, USA, December 2-7, 2025 / Mexico City, Mexico, November 30 - December 5, 2025, 2025)

Fast Monte Carlo Tree Diffusion: 100 exttimes Speedup via Parallel and Sparse Planning - Jaesik Yoon; Hyeonseo Cho; Yoshua Bengio; Sungjin Ahn (Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, NeurIPS 2025, San Diago, CA, USA, December 2-7, 2025 / Mexico City, Mexico, November 30 - December 5, 2025, 2025)

Can a Bayesian Oracle Prevent Harm from an Agent? - Yoshua Bengio; Michael K. Cohen; Nikolay Malkin; Matt MacDermott; Damiano Fornasiere; Pietro Greiner; Younesse Kaddar (Conference on Uncertainty in Artificial Intelligence, Rio Othon Palace, Rio de Janeiro, Brazil, 21-25 July 2025, 2025)

RL, but don't do anything I wouldn't do - Michael K. Cohen; Marcus Hutter; Yoshua Bengio; Stuart Russell (Conference on Uncertainty in Artificial Intelligence, Rio Othon Palace, Rio de Janeiro, Brazil, 21-25 July 2025, 2025)

EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision - Diego A. Velázquez; Pau Rodríguez López; Sergio Alonso; Josep M. Gonfaus; Jordi Gonzàlez; Gerardo Richarte; Javier Marín; Yoshua Bengio; Alexandre Lacoste (IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025 - Workshops, Tucson, AZ, USA, February 28 - March 4, 2025, 2025)

EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision - Diego A. Velázquez; Pau Rodríguez López; Sergio Alonso; Josep M. Gonfaus; Jordi Gonzàlez; Gerardo Richarte; Javier Marín; Yoshua Bengio; Alexandre Lacoste (CoRR, 2025)

Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity - David Williams-King; Linh Le; Adam Oberman; Yoshua Bengio (CoRR, 2025)

International AI Safety Report - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi; Philip Fox; Ben Garfinkel; Danielle Goldfarb; Hoda Heidari; Anson Ho; et al. (CoRR, 2025)

AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding - Ahmed Masry; Juan A. Rodríguez; Tianyu Zhang; Suyuchen Wang; Chao Wang; Aarash Feizi; Akshay Kalkunte Suresh; Abhay Puri; Xiangru Jian; Pierre-André Noël; Sathwik Tejaswi Madhusudhan; Marco Pedersoli; et al. (CoRR, 2025)

A physics-based data-driven model for CO\(_2\) gas diffusion electrodes to drive automated laboratories - Ivan Grega; Félix Therrien; Abhishek Soni; Karry Ocean; Kevan Dettelbach; Ribwar Ahmadi; Mehrdad Mokhtari; Curtis P. Berlinguette; Yoshua Bengio (CoRR, 2025)

Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models - Siddarth Venkatraman; Mohsin Hasan; Minsu Kim; Luca Scimeca; Marcin Sendera; Yoshua Bengio; Glen Berseth; Nikolay Malkin (CoRR, 2025)

Monte Carlo Tree Diffusion for System 2 Planning - Jaesik Yoon; Hyeonseo Cho; Doojin Baek; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control - Thomas Jiralerspong; Berton Earnshaw; Jason S. Hartford; Yoshua Bengio; Luca Scimeca (CoRR, 2025)

In-Context Parametric Inference: Point or Distribution Estimators? - Sarthak Mittal; Yoshua Bengio; Nikolay Malkin; Guillaume Lajoie (CoRR, 2025)

OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes - Félix Therrien; Jamal Abou Haibeh; Divya Sharma; Rhiannon Hendley; Alex Hernández-García; Sun Sun; Alain Tchagang; Jiang Su; Samuel Huberman; Yoshua Bengio; Hongyu Guo; Homin Shin (CoRR, 2025)

Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path? - Yoshua Bengio; Michael K. Cohen; Damiano Fornasiere; Joumana Ghosn; Pietro Greiner; Matt MacDermott; Sören Mindermann; Adam Oberman; Jesse Richardson; Oliver Richardson; Marc-Antoine Rondeau; Pierre-Luc St-Charles; et al. (CoRR, 2025)

Learning Decision Trees as Amortized Structure Inference - Mohammed Mahfoud; Ghait Boukachab; Michal Koziarski; Alex Hernández-García; Stefan Bauer; Yoshua Bengio; Nikolay Malkin (CoRR, 2025)

Solving Bayesian inverse problems with diffusion priors and off-policy RL - Luca Scimeca; Siddarth Venkatraman; Moksh Jain; Minsu Kim; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (CoRR, 2025)

Offline Model-Based Optimization: Comprehensive Review - Minsu Kim; Jiayao Gu; Ye Yuan; Taeyoung Yun; Zixuan Liu; Yoshua Bengio; Can Chen (CoRR, 2025)

Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training - Brian R. Bartoldson; Siddarth Venkatraman; James Diffenderfer; Moksh Jain; Tal Ben-Nun; Seanie Lee; Minsu Kim; Johan S. Obando-Ceron; Yoshua Bengio; Bhavya Kailkhura (CoRR, 2025)

A scalable gene network model of regulatory dynamics in single cells - Paul Bertin; Joseph D. Viviano; Alejandro Tejada-Lapuerta; Weixu Wang; Stefan Bauer; Fabian J. Theis; Yoshua Bengio (CoRR, 2025)

Extendable Long-Horizon Planning via Hierarchical Multiscale Diffusion - Chang Chen; Hany Hamed; Doojin Baek; Taegu Kang; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery - Mélisande Teng; Arthur Ouaknine; Etienne Laliberté; Yoshua Bengio; David Rolnick; Hugo Larochelle (CoRR, 2025)

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? - Ben Bucknall; Saad Siddiqui; Lara Thurnherr; Conor McGurk; Ben Harack; Anka Reuel; Patricia Paskov; Casey Mahoney; Sören Mindermann; Scott Singer; Vinay Hiremath; Charbel-Raphaël Ségerie; et al. (CoRR, 2025)

Search-Based Correction of Reasoning Chains for Language Models - Minsu Kim; Jean-Pierre R. Falet; Oliver E. Richardson; Xiaoyin Chen; Moksh Jain; Sungjin Ahn; Sungsoo Ahn; Yoshua Bengio (CoRR, 2025)

Adaptive Cyclic Diffusion for Inference Scaling - Gyubin Lee; Truong Nhat Nguyen Bao; Jaesik Yoon; Dongwoo Lee; Minsu Kim; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

Self-Evolving Curriculum for LLM Reasoning - Xiaoyin Chen; Jiarui Lu; Minsu Kim; Dinghuai Zhang; Jian Tang; Alexandre Piché; Nicolas Gontier; Yoshua Bengio; Ehsan Kamalloo (CoRR, 2025)

Structure-Aligned Protein Language Model - Can Chen; David Heurtel-Depeiges; Robert M. Vernon; Christopher James Langmead; Yoshua Bengio; Quentin Fournier (CoRR, 2025)

FORT: Forward-Only Regression Training of Normalizing Flows - Danyal Rehman; Oscar Davis; Jiarui Lu; Jian Tang; Michael M. Bronstein; Yoshua Bengio; Alexander Tong; Avishek Joey Bose (CoRR, 2025)

Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery - Mélisande Teng; Arthur Ouaknine; Etienne Laliberté; Yoshua Bengio; David Rolnick; Hugo Larochelle (CoRR, 2025)

Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning - Jaesik Yoon; Hyeonseo Cho; Yoshua Bengio; Sungjin Ahn (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety - Tomek Korbak; Mikita Balesni; Elizabeth Barnes; Yoshua Bengio; Joe Benton; Joseph Bloom; Mark Chen; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)

Torsional-GFN: a conditional conformation generator for small molecules - Alexandra Volokhova; Léna Néhale Ezzine; Piotr Gainski; Luca Scimeca; Emmanuel Bengio; Prudencio Tossou; Yoshua Bengio; Alex Hernández-García (CoRR, 2025)

Expert-Guided LLM Reasoning for Battery Discovery: From AI-Driven Hypothesis to Synthesis and Characterization - Shengchao Liu; Hannan Xu; Yan Ai; Huanxin Li; Yoshua Bengio; Harry Guo (CoRR, 2025)

Relative Trajectory Balance is equivalent to Trust-PCL - Tristan Deleu; Padideh Nouri; Yoshua Bengio; Doina Precup (CoRR, 2025)

Active Attacks: Red-teaming LLMs via Adaptive Environments - Taeyoung Yun; Pierre-Luc St-Charles; Jinkyoo Park; Yoshua Bengio; Minsu Kim (CoRR, 2025)

Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models - Siddarth Venkatraman; Vineet Jain; Sarthak Mittal; Vedant Shah; Johan S. Obando-Ceron; Yoshua Bengio; Brian R. Bartoldson; Bhavya Kailkhura; Guillaume Lajoie; Glen Berseth; Nikolay Malkin; Moksh Jain (CoRR, 2025)

Catalyst GFlowNet for electrocatalyst design: A hydrogen evolution reaction case study - Lena Podina; Christina Humer; Alexandre Duval; Victor Schmidt; Ali Ramlaoui; Shahana Chatterjee; Yoshua Bengio; Alex Hernández-García; David Rolnick; Félix Therrien (CoRR, 2025)

Learning What Matters: Steering Diffusion via Spectrally Anisotropic Forward Noise - Luca Scimeca; Thomas Jiralerspong; Berton Earnshaw; Jason S. Hartford; Yoshua Bengio (CoRR, 2025)

Scope: Selective Cross-modal Orchestration of Visual Perception Experts - Tianyu Zhang; Suyuchen Wang; Chao Wang; Juan A. Rodríguez; Ahmed Masry; Xiangru Jian; Yoshua Bengio; Perouz Taslakian (CoRR, 2025)

International AI Safety Report 2025: First Key Update: Capabilities and Risk Implications - Yoshua Bengio; Stephen Clare; Carina Prunkl; Shalaleh Rismani; Maksym Andriushchenko; Ben Bucknall; Philip Fox; Tiancheng Hu; Cameron Jones; Sam Manning; Nestor Maslej; Vasilios Mavroudis; et al. (CoRR, 2025)

A Definition of AGI - Dan Hendrycks; Dawn Song; Christian Szegedy; Honglak Lee; Yarin Gal; Erik Brynjolfsson; Sharon Li; Andy Zou; Lionel Levine; Bo Han; Jie Fu; Ziwei Liu; et al. (CoRR, 2025)

Surrogate-based quantification of policy uncertainty in generative flow networks - Ramón Dineth Nartallo-Kaluarachchi; Robert Manson-Sawko; Shashanka Ubaru; Dongsung Huh; Malgorzata J. Zimon; Lior Horesh; Yoshua Bengio (CoRR, 2025)

Scaling Latent Reasoning via Looped Language Models - Rui-Jie Zhu; Zixuan Wang; Kai Hua; Tianyu Zhang; Ziniu Li; Haoran Que; Boyi Wei; Zixin Wen; Fan Yin; He Xing; Lu Li; Jiajun Shi; et al. (CoRR, 2025)

International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management - Yoshua Bengio; Stephen Clare; Carina Prunkl; Maksym Andriushchenko; Ben Bucknall; Philip Fox; Nestor Maslej; Conor McGlynn; Malcolm Murray; Shalaleh Rismani; Stephen Casper; Jessica Newman; et al. (CoRR, 2025)

FALCON: Few-step Accurate Likelihoods for Continuous Flows - Danyal Rehman; Tara Akhound-Sadegh; Artem Gazizov; Yoshua Bengio; Alexander Tong (CoRR, 2025)

Sliding Window Recurrences for Sequence Models - Dragos Secrieru; Garyk Brixi; Yoshua Bengio; Taiji Suzuki; Michael Poli; Stefano Massaroli (CoRR, 2025)

A Comedy of Estimators: On KL Regularization in RL Training of LLMs - Vedant Shah; Johan S. Obando-Ceron; Vineet Jain; Brian R. Bartoldson; Bhavya Kailkhura; Sarthak Mittal; Glen Berseth; Pablo Samuel Castro; Yoshua Bengio; Nikolay Malkin; Moksh Jain; Siddarth Venkatraman; et al. (CoRR, 2025)

AI content detection in the emerging information ecosystem: new obligations for media and tech companies - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design - Alexandre Duval; Victor Schmidt; Santiago Miret; Yoshua Bengio; Alex Hernández-García; David Rolnick (J. Mach. Learn. Res., 2024)

Improving and generalizing flow-based generative models with minibatch optimal transport - Alexander Tong; Kilian Fatras; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Guy Wolf; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (Trans. Mach. Learn. Res., 2024)

Multi-Fidelity Active Learning with GFlowNets - Alex Hernández-García; Nikita Saxena; Moksh Jain; Cheng-Hao Liu; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Distributional GFlowNets with Quantile Flows - Dinghuai Zhang; Ling Pan; Ricky T. Q. Chen; Aaron C. Courville; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Regeneration Learning: A Learning Paradigm for Data Generation - Xu Tan; Tao Qin; Jiang Bian; Tie-Yan Liu; Yoshua Bengio (Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2024, February 20-27, 2024, Vancouver, Canada, 2024)

Simulation-Free Schrödinger Bridges via Score and Flow Matching - Alexander Tong; Nikolay Malkin; Kilian Fatras; Lazar Atanackovic; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Yoshua Bengio (International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain, 2024)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning - Harry Zhao; Safa Alver; Harm van Seijen; Romain Laroche; Doina Precup; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Cycle Consistency Driven Object Discovery - Aniket Rajiv Didolkar; Anirudh Goyal; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Delta-AI: Local objectives for amortized inference in sparse graphical models - Jean-Pierre R. Falet; Hae Beom Lee; Nikolay Malkin; Chen Sun; Dragos Secrieru; Dinghuai Zhang; Guillaume Lajoie; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Tree Cross Attention - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Amortizing intractable inference in large language models - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Expected flow networks in stochastic environments and two-player zero-sum games - Marco Jiralerspong; Bilun Sun; Danilo Vucetic; Tianyu Zhang; Yoshua Bengio; Gauthier Gidel; Nikolay Malkin (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Local Search GFlowNets - Minsu Kim; Taeyoung Yun; Emmanuel Bengio; Dinghuai Zhang; Yoshua Bengio; Sungsoo Ahn; Jinkyoo Park (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Object centric architectures enable efficient causal representation learning - Amin Mansouri; Jason S. Hartford; Yan Zhang; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Pre-Training and Fine-Tuning Generative Flow Networks - Ling Pan; Moksh Jain; Kanika Madan; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization - Dinghuai Zhang; Ricky T. Q. Chen; Cheng-Hao Liu; Aaron C. Courville; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

PhyloGFN: Phylogenetic inference with generative flow networks - Ming-Yang Zhou; Zichao Yan; Elliot Layne; Nikolay Malkin; Dinghuai Zhang; Moksh Jain; Mathieu Blanchette; Yoshua Bengio (The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024, 2024)

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities - Tara Akhound-Sadegh; Jarrid Rector-Brooks; Avishek Joey Bose; Sarthak Mittal; Pablo Lemos; Cheng-Hao Liu; Marcin Sendera; Siamak Ravanbakhsh; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Alexander Tong (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Memory Efficient Neural Processes via Constant Memory Attention Block - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Learning to Scale Logits for Temperature-Conditional GFlowNets - Minsu Kim; Joohwan Ko; Taeyoung Yun; Dinghuai Zhang; Ling Pan; Woochang Kim; Jinkyoo Park; Emmanuel Bengio; Yoshua Bengio (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Improving Gradient-Guided Nested Sampling for Posterior Inference - Pablo Lemos; Nikolay Malkin; Will Handley; Yoshua Bengio; Yashar Hezaveh; Laurence Perreault Levasseur (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization - Milos Nikolic; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Omar Mohamed Awad; Isak Edo Vivancos; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (IEEE International Symposium on Circuits and Systems, ISCAS 2024, Singapore, May 19-22, 2024, 2024)

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Siyuan Guo; Michal Valko; Timothy P. Lillicrap; Danilo Jimenez Rezende; Yoshua Bengio; Michael C. Mozer; Sanjeev Arora (Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets - Michal Koziarski; Andrei Rekesh; Dmytro Shevchuk; Almer van der Sloot; Piotr Gainski; Yoshua Bengio; Cheng-Hao Liu; Mike Tyers; Robert A. Batey (Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

Improved off-policy training of diffusion samplers - Marcin Sendera; Minsu Kim; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

Amortizing intractable inference in diffusion models for vision, language, and control - Siddarth Venkatraman; Moksh Jain; Luca Scimeca; Minsu Kim; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

Trajectory Flow Matching with Applications to Clinical Time Series Modelling - Xi Zhang; Yuan Pu; Yuki Kawamura; Andrew Loza; Yoshua Bengio; Dennis L. Shung; Alexander Tong (Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024)

Discrete Probabilistic Inference as Control in Multi-path Environments - Tristan Deleu; Padideh Nouri; Nikolay Malkin; Doina Precup; Yoshua Bengio (Uncertainty in Artificial Intelligence, 15-19 July 2024, Universitat Pompeu Fabra, Barcelona, Spain, 2024)

Efficient Causal Graph Discovery Using Large Language Models - Thomas Jiralerspong; Xiaoyin Chen; Yash More; Vedant Shah; Yoshua Bengio (CoRR, 2024)

On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling - Marcin Sendera; Minsu Kim; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (CoRR, 2024)

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities - Tara Akhound-Sadegh; Jarrid Rector-Brooks; Avishek Joey Bose; Sarthak Mittal; Pablo Lemos; Cheng-Hao Liu; Marcin Sendera; Siamak Ravanbakhsh; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Alexander Tong (CoRR, 2024)

Computing Power and the Governance of Artificial Intelligence - Girish Sastry; Lennart Heim; Haydn Belfield; Markus Anderljung; Miles Brundage; Julian Hazell; Cullen O'Keefe; Gillian K. Hadfield; Richard Ngo; Konstantin Pilz; George Gor; Emma Bluemke; et al. (CoRR, 2024)

Discrete Probabilistic Inference as Control in Multi-path Environments - Tristan Deleu; Padideh Nouri; Nikolay Malkin; Doina Precup; Yoshua Bengio (CoRR, 2024)

Machine learning and information theory concepts towards an AI Mathematician - Yoshua Bengio; Nikolay Malkin (CoRR, 2024)

Ant Colony Sampling with GFlowNets for Combinatorial Optimization - Minsu Kim; Sanghyeok Choi; Jiwoo Son; Hyeonah Kim; Jinkyoo Park; Yoshua Bengio (CoRR, 2024)

Language Models Can Reduce Asymmetry in Information Markets - Nasim Rahaman; Martin Weiss; Manuel Wüthrich; Yoshua Bengio; Li Erran Li; Chris Pal; Bernhard Schölkopf (CoRR, 2024)

Foundational Challenges in Assuring Alignment and Safety of Large Language Models - Usman Anwar; Abulhair Saparov; Javier Rando; Daniel Paleka; Miles Turpin; Peter Hase; Ekdeep Singh Lubana; Erik Jenner; Stephen Casper; Oliver Sourbut; Benjamin L. Edelman; Zhaowei Zhang; et al. (CoRR, 2024)

Towards DNA-Encoded Library Generation with GFlowNets - Michal Koziarski; Mohammed Abukalam; Vedant Shah; Louis Vaillancourt; Doris Alexandra Schuetz; Moksh Jain; Almer van der Sloot; Mathieu Bourgey; Anne Marinier; Yoshua Bengio (CoRR, 2024)

Generative Active Learning for the Search of Small-molecule Protein Binders - Maksym Korablyov; Cheng-Hao Liu; Moksh Jain; Almer M. van der Sloot; Eric Jolicoeur; Edward Ruediger; Andrei Cristian Nica; Emmanuel Bengio; Kostiantyn Lapchevskyi; Daniel St-Cyr; Doris Alexandra Schuetz; Victor Ion Butoi; et al. (CoRR, 2024)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell; Max Tegmark; Sanjit A. Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (CoRR, 2024)

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving - Aniket Didolkar; Anirudh Goyal; Nan Rosemary Ke; Siyuan Guo; Michal Valko; Timothy P. Lillicrap; Danilo J. Rezende; Yoshua Bengio; Michael Mozer; Sanjeev Arora (CoRR, 2024)

Divergent Creativity in Humans and Large Language Models - Antoine Bellemare-Pépin; François Lespinasse; Philipp Thölke; Yann Harel; Kory W. Mathewson; Jay A. Olson; Yoshua Bengio; Karim Jerbi (CoRR, 2024)

Attention as an RNN - Leo Feng; Frederick Tung; Hossein Hajimirsadeghi; Mohamed Osama Ahmed; Yoshua Bengio; Greg Mori (CoRR, 2024)

Learning diverse attacks on large language models for robust red-teaming and safety tuning - Seanie Lee; Minsu Kim; Lynn Cherif; David Dobre; Juho Lee; Sung Ju Hwang; Kenji Kawaguchi; Gauthier Gidel; Yoshua Bengio; Nikolay Malkin; Moksh Jain (CoRR, 2024)

Amortizing intractable inference in diffusion models for vision, language, and control - Siddarth Venkatraman; Moksh Jain; Luca Scimeca; Minsu Kim; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (CoRR, 2024)

Baking Symmetry into GFlowNets - George Ma; Emmanuel Bengio; Yoshua Bengio; Dinghuai Zhang (CoRR, 2024)

VCR: Visual Caption Restoration - Tianyu Zhang; Suyuchen Wang; Lu Li; Ge Zhang; Perouz Taslakian; Sai Rajeswar; Jie Fu; Bang Liu; Yoshua Bengio (CoRR, 2024)

MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation - Lu Li; Tianyu Zhang; Zhiqi Bu; Suyuchen Wang; Huan He; Jie Fu; Yonghui Wu; Jiang Bian; Yong Chen; Yoshua Bengio (CoRR, 2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets - Michal Koziarski; Andrei Rekesh; Dmytro Shevchuk; Almer van der Sloot; Piotr Gainski; Yoshua Bengio; Cheng-Hao Liu; Mike Tyers; Robert A. Batey (CoRR, 2024)

On Generalization for Generative Flow Networks - Anas Krichel; Nikolay Malkin; Salem Lahlou; Yoshua Bengio (CoRR, 2024)

Open Problems in Technical AI Governance - Anka Reuel; Ben Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (CoRR, 2024)

AI-Assisted Generation of Difficult Math Questions - Vedant Shah; Dingli Yu; Kaifeng Lyu; Simon Park; Nan Rosemary Ke; Michael Mozer; Yoshua Bengio; Sanjeev Arora; Anirudh Goyal (CoRR, 2024)

Cell Morphology-Guided Small Molecule Generation with GFlowNets - Stephen Zhewen Lu; Ziqing Lu; Ehsan Hajiramezanali; Tommaso Biancalani; Yoshua Bengio; Gabriele Scalia; Michal Koziarski (CoRR, 2024)

Can a Bayesian Oracle Prevent Harm from an Agent? - Yoshua Bengio; Michael K. Cohen; Nikolay Malkin; Matt MacDermott; Damiano Fornasiere; Pietro Greiner; Younesse Kaddar (CoRR, 2024)

Zero-Shot Object-Centric Representation Learning - Aniket Didolkar; Andrii Zadaianchuk; Anirudh Goyal; Michael C. Mozer; Yoshua Bengio; Georg Martius; Maximilian Seitzer (CoRR, 2024)

Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold - Lazar Atanackovic; Xi Zhang; Brandon Amos; Mathieu Blanchette; Leo J. Lee; Yoshua Bengio; Alexander Tong; Kirill Neklyudov (CoRR, 2024)

Were RNNs All We Needed? - Leo Feng; Frederick Tung; Mohamed Osama Ahmed; Yoshua Bengio; Hossein Hajimirsadeghi (CoRR, 2024)

Adaptive teachers for amortized samplers - Minsu Kim; Sanghyeok Choi; Taeyoung Yun; Emmanuel Bengio; Leo Feng; Jarrid Rector-Brooks; Sungsoo Ahn; Jinkyoo Park; Nikolay Malkin; Yoshua Bengio (CoRR, 2024)

Geometric Signatures of Compositionality Across a Language Model's Lifetime - Jin Hwa Lee; Thomas Jiralerspong; Lei Yu; Yoshua Bengio; Emily Cheng (CoRR, 2024)

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models - Seanie Lee; Haebin Seong; Dong Bok Lee; Minki Kang; Xiaoyin Chen; Dominik Wagner; Yoshua Bengio; Juho Lee; Sung Ju Hwang (CoRR, 2024)

RL, but don't do anything I wouldn't do - Michael K. Cohen; Marcus Hutter; Yoshua Bengio; Stuart Russell (CoRR, 2024)

Identifying and Addressing Delusions for Target-Directed Decision-Making - Mingde Zhao; Tristan Sylvain; Doina Precup; Yoshua Bengio (CoRR, 2024)

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction - Jarrid Rector-Brooks; Mohsin Hasan; Zhangzhi Peng; Zachary Quinn; Cheng-Hao Liu; Sarthak Mittal; Nouha Dziri; Michael M. Bronstein; Yoshua Bengio; Pranam Chatterjee; Alexander Tong; Avishek Joey Bose (CoRR, 2024)

A Complexity-Based Theory of Compositionality - Eric Elmoznino; Thomas Jiralerspong; Yoshua Bengio; Guillaume Lajoie (CoRR, 2024)

Action abstractions for amortized sampling - Oussama Boussif; Léna Néhale Ezzine; Joseph D. Viviano; Michal Koziarski; Moksh Jain; Nikolay Malkin; Emmanuel Bengio; Rim Assouel; Yoshua Bengio (CoRR, 2024)

Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases - Cristian Meo; Akihiro Nakano; Mircea Lica; Aniket Didolkar; Masahiro Suzuki; Anirudh Goyal; Mengmi Zhang; Justin Dauwels; Yutaka Matsuo; Yoshua Bengio (CoRR, 2024)

Structure Language Models for Protein Conformation Generation - Jiarui Lu; Xiaoyin Chen; Stephen Zhewen Lu; Chence Shi; Hongyu Guo; Yoshua Bengio; Jian Tang (CoRR, 2024)

Trajectory Flow Matching with Applications to Clinical Time Series Modeling - Xi Zhang; Yuan Pu; Yuki Kawamura; Andrew Loza; Yoshua Bengio; Dennis L. Shung; Alexander Tong (CoRR, 2024)

Imagining and building wise machines: The centrality of AI metacognition - Samuel G. B. Johnson; Amir-Hossein Karimi; Yoshua Bengio; Nick Chater; Tobias Gerstenberg; Kate Larson; Sydney Levine; Melanie Mitchell; Iyad Rahwan; Bernhard Schölkopf; Igor Grossmann (CoRR, 2024)

BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks - Juan A. Rodríguez; Xiangru Jian; Siba Smarak Panigrahi; Tianyu Zhang; Aarash Feizi; Abhay Puri; Akshay Kalkunte; François Savard; Ahmed Masry; Shravan Nayak; Rabiul Awal; Mahsa Massoud; et al. (CoRR, 2024)

International Scientific Report on the Safety of Advanced AI (Interim Report) - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi; Danielle Goldfarb; Hoda Heidari; Leila Khalatbari; Shayne Longpre; Vasilios Mavroudis; et al. (CoRR, 2024)

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets - Zhen Liu; Tim Z. Xiao; Weiyang Liu; Yoshua Bengio; Dinghuai Zhang (CoRR, 2024)

Tackling Climate Change with Machine Learning - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Sasha Luccioni; Tegan Maharaj; et al. (ACM Comput. Surv., 2023)

Generative AI models should include detection mechanisms as a condition for public release - Alistair Knott; Dino Pedreschi; Raja Chatila; Tapabrata Chakraborti; Susan Leavy; Ricardo Baeza-Yates; David M. Eyers; Andrew Trotman; Paul D. Teal; Przemyslaw Biecek; Stuart Russell; Yoshua Bengio (Ethics Inf. Technol., 2023)

Benchmarking Graph Neural Networks - Vijay Prakash Dwivedi; Chaitanya K. Joshi; Anh Tuan Luu; Thomas Laurent; Yoshua Bengio; Xavier Bresson (J. Mach. Learn. Res., 2023)

GFlowNet Foundations - Yoshua Bengio; Salem Lahlou; Tristan Deleu; Edward J. Hu; Mo Tiwari; Emmanuel Bengio (J. Mach. Learn. Res., 2023)

Scientific discovery in the age of artificial intelligence - Hanchen Wang; Tianfan Fu; Yuanqi Du; Wenhao Gao; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Neural Causal Structure Discovery from Interventions - Nan Rosemary Ke; Olexa Bilaniuk; Anirudh Goyal; Stefan Bauer; Hugo Larochelle; Bernhard Schölkopf; Michael Curtis Mozer; Christopher Pal; Yoshua Bengio (Trans. Mach. Learn. Res., 2023)

DEUP: Direct Epistemic Uncertainty Prediction - Salem Lahlou; Moksh Jain; Hadi Nekoei; Victor Butoi; Paul Bertin; Jarrid Rector-Brooks; Maksym Korablyov; Yoshua Bengio (Trans. Mach. Learn. Res., 2023)

The Effect of Diversity in Meta-Learning - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023, 2023)

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness - Dianbo Liu; Alex Lamb; Xu Ji; Pascal Tikeng Notsawo Jr.; Michael Mozer; Yoshua Bengio; Kenji Kawaguchi (Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023, 2023)

Combining Parameter-efficient Modules for Task-level Generalisation - Edoardo Maria Ponti; Alessandro Sordoni; Yoshua Bengio; Siva Reddy (Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2023, Dubrovnik, Croatia, May 2-6, 2023, 2023)

Latent Bottlenecked Attentive Neural Processes - Leo Feng; Hossein Hajimirsadeghi; Yoshua Bengio; Mohamed Osama Ahmed (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning - Dianbo Liu; Vedant Shah; Oussama Boussif; Cristian Meo; Anirudh Goyal; Tianmin Shu; Michael Curtis Mozer; Nicolas Heess; Yoshua Bengio (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

GFlowNets and variational inference - Nikolay Malkin; Salem Lahlou; Tristan Deleu; Xu Ji; Edward J. Hu; Katie Everett; Dinghuai Zhang; Yoshua Bengio (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Generative Augmented Flow Networks - Ling Pan; Dinghuai Zhang; Aaron C. Courville; Longbo Huang; Yoshua Bengio (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Predictive Inference with Feature Conformal Prediction - Jiaye Teng; Chuan Wen; Dinghuai Zhang; Yoshua Bengio; Yang Gao; Yang Yuan (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Latent State Marginalization as a Low-cost Approach for Improving Exploration - Dinghuai Zhang; Aaron C. Courville; Yoshua Bengio; Qinqing Zheng; Amy Zhang; Ricky T. Q. Chen (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Robust and Controllable Object-Centric Learning through Energy-based Models - Ruixiang Zhang; Tong Che; Boris Ivanovic; Renhao Wang; Marco Pavone; Yoshua Bengio; Liam Paull (The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023)

Interventional Causal Representation Learning - Kartik Ahuja; Divyat Mahajan; Yixin Wang; Yoshua Bengio (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

FAENet: Frame Averaging Equivariant GNN for Materials Modeling - Alexandre Duval; Victor Schmidt; Alex Hernández-García; Santiago Miret; Fragkiskos D. Malliaros; Yoshua Bengio; David Rolnick (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

GFlowNet-EM for Learning Compositional Latent Variable Models - Edward J. Hu; Nikolay Malkin; Moksh Jain; Katie E. Everett; Alexandros Graikos; Yoshua Bengio (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Multi-Objective GFlowNets - Moksh Jain; Sharath Chandra Raparthy; Alex Hernández-García; Jarrid Rector-Brooks; Yoshua Bengio; Santiago Miret; Emmanuel Bengio (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Equivariance with Learned Canonicalization Functions - Sékou-Oumar Kaba; Arnab Kumar Mondal; Yan Zhang; Yoshua Bengio; Siamak Ravanbakhsh (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

A theory of continuous generative flow networks - Salem Lahlou; Tristan Deleu; Pablo Lemos; Dinghuai Zhang; Alexandra Volokhova; Alex Hernández-García; Léna Néhale Ezzine; Yoshua Bengio; Nikolay Malkin (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

GFlowOut: Dropout with Generative Flow Networks - Dianbo Liu; Moksh Jain; Bonaventure F. P. Dossou; Qianli Shen; Salem Lahlou; Anirudh Goyal; Nikolay Malkin; Chris Chinenye Emezue; Dinghuai Zhang; Nadhir Hassen; Xu Ji; Kenji Kawaguchi; et al. (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Learning GFlowNets From Partial Episodes For Improved Convergence And Stability - Kanika Madan; Jarrid Rector-Brooks; Maksym Korablyov; Emmanuel Bengio; Moksh Jain; Andrei Cristian Nica; Tom Bosc; Yoshua Bengio; Nikolay Malkin (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Better Training of GFlowNets with Local Credit and Incomplete Trajectories - Ling Pan; Nikolay Malkin; Dinghuai Zhang; Yoshua Bengio (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Hyena Hierarchy: Towards Larger Convolutional Language Models - Michael Poli; Stefano Massaroli; Eric Nguyen; Daniel Y. Fu; Tri Dao; Stephen Baccus; Yoshua Bengio; Stefano Ermon; Christopher Ré (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)

Discrete Key-Value Bottleneck - Frederik Träuble; Anirudh Goyal; Nasim Rahaman; Michael Curtis Mozer; Kenji Kawaguchi; Yoshua Bengio; Bernhard Schölkopf (International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 2023)